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AI's next frontier: Mamba, JEPA, and Diffusion Models poised to replace transformers

By PulseAugur Editorial · [1 sources] ·

The AI landscape is experiencing a cyclical shift, with transformers, dominant since 2017, potentially being replaced by newer architectures like state space models (Mamba) and Joint Embedding Predictive Architectures (JEPA). This transition is driven by limitations in transformers, such as quadratic scaling issues with long contexts, diminishing returns in training data, high energy costs, and a fundamental inability to achieve true understanding beyond pattern matching. Emerging models like Gemini Diffusion, Nvidia's Nemotron 3, and Qwen 3.5 are already incorporating elements of these next-generation designs, signaling a move towards hybrid systems expected in production by 2027. AI

IMPACT Suggests a potential shift away from transformers, impacting future AI development and infrastructure choices.

RANK_REASON Article discusses trends and potential future architectures in AI research rather than a specific release or event.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI's next frontier: Mamba, JEPA, and Diffusion Models poised to replace transformers

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Article discusses trends and potential future architectures in AI research rather than a specific release or event.
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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model release, infra
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Rost ·

    What Comes After LLMs? Mamba, Diffusion & World Models

    <p>AI hype follows a rhythm: roughly every three years, the architecture everyone is betting on gets replaced by something newer. The next shift is already forming in research labs.</p> <p>What follows is a tour of the strongest candidates to replace the transformer, and of the e…

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